Pipe image feature analysis using calibration data

ABSTRACT

One aspect provides a method, including: displaying, at a display screen, an image of an interior of a pipe, the image being obtained using a pipe inspection robot; accessing, using a processor, calibration data associated with the image; receiving, via an input device, user input marking at least a portion of the image; determining, using a processor, quantitative pipe feature data for at least one feature of the pipe using the marking and the calibration data; and providing, based on the determining, data associated with the at least one feature. Other aspects are described and claimed.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Patent ApplicationSer. No. 62/583,683, having the same title and filed on Nov. 9, 2017,the contents of which are incorporated by reference in their entirety.

FIELD

The subject matter described herein relates to collection and use ofimage data of an interior of a pipe to identify and quantify pipefeatures.

BACKGROUND

Pipes that carry water, other fluids, and gases are an important type ofinfrastructure. Pipes are often inspected as a matter of routine upkeepor in response to a noticed issue. Various systems and methods exist togather pipe inspection data. For example, pipe infrastructure data maybe obtained by using one or more cameras operatively coupled to a pipeinspection robot that is capable of traversing through a pipe. The oneor more cameras are capable of capturing image data (e.g., still images,video, etc.) of visible defects located within a pipe, pipe connections,and the like. The image data may then be viewed by a user (e.g., live asthe image data is being captured, at a later time after the image datahas been captured, etc.) to determine the type, severity, and locationof the defect, pipe connections, pipe features, and the like.

BRIEF SUMMARY

In summary, one aspect provides a method, comprising: displaying, at adisplay screen, an image of an interior of a pipe, the image beingobtained using a pipe inspection robot; accessing, using a processor,calibration data associated with the image; receiving, via an inputdevice, user input marking at least a portion of the image; determining,using a processor, quantitative pipe feature data for at least onefeature of the pipe using the marking and the calibration data; andproviding, based on the determining, data associated with the at leastone feature.

Another aspect provides a system, comprising: an information handlingdevice comprising a display screen, an input device, a processor, and amemory device that stores instructions executable by the processor to:display, at the display screen, an image of an interior of a pipe, theimage being obtained using a pipe inspection robot; access calibrationdata associated with the image; receive, via the input device, userinput marking at least a portion of the image; determine quantitativepipe feature data for at least one feature of the pipe using the markingand the calibration data; and provide, based on the determination of thequantitative pipe feature data, data associated with the at least onefeature.

A further aspect provides a product, comprising: a non-transitorystorage device that stores code executable by a processor, the codecomprising: code that displays, at a display screen, an image of aninterior of a pipe, the image being obtained using a pipe inspectionrobot; code that accesses calibration data associated with the image;code that receives user input marking at least a portion of the image;code that determines quantitative pipe feature data for at least onefeature associated with the pipe using the marking and the calibrationdata; and code that provides, based on the determination of thequantitative pipe feature data, data associated with the at least onefeature.

The foregoing is a summary and thus may contain simplifications,generalizations, and omissions of detail; consequently, those skilled inthe art will appreciate that the summary is illustrative only and is notintended to be in any way limiting.

For a better understanding of the embodiments, together with other andfurther features and advantages thereof, reference is made to thefollowing description, taken in conjunction with the accompanyingdrawings. The scope of the invention will be pointed out in the appendedclaims.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 illustrates an example pipe inspection robot according to anembodiment.

FIG. 2 illustrates an example method of calibrating according to anembodiment.

FIG. 3 illustrates an example method of outputting calibrated data foran image according to an embodiment.

FIG. 4 illustrates an example image markup according to an embodiment.

FIG. 5 illustrates an example computing device according to anembodiment.

DETAILED DESCRIPTION

It will be readily understood that the components of the embodiments, asgenerally described and illustrated in the figures herein, may bearranged and designed in a wide variety of different configurations inaddition to the described example embodiments. Thus, the following moredetailed description of the example embodiments, as represented in thefigures, is not intended to limit the scope of the claims, but is merelyrepresentative of those embodiments.

Reference throughout this specification to “embodiment(s)” (or the like)means that a particular feature, structure, or characteristic describedin connection with the embodiment is included in at least oneembodiment. Thus, appearances of the phrases “according to embodiments”or “an embodiment” (or the like) in various places throughout thisspecification are not necessarily all referring to the same embodiment.

Furthermore, the described features, structures, or characteristics maybe combined in any suitable manner in one or more embodiments. In thefollowing description, numerous specific details are provided to give athorough understanding of example embodiments. One skilled in therelevant art will recognize, however, that aspects can be practicedwithout one or more of the specific details, or with other methods,components, materials, etc. In other instances, well-known structures,materials, or operations are not shown or described in detail to avoidobfuscation.

Image data (e.g., still image data, video data, etc.) captured by one ormore image sensors, such as visible light cameras or other imagesensors, of a pipe inspection robot may be viewed by a user to identifypipe features such as pipe defects (e.g., cracks, root intrusion,sediment buildup, etc.) located inside of a pipe. In addition tocontrolling the movement of the pipe inspection robot, users are capableof remotely controlling the cameras (e.g., by utilizing pan and tiltfunctions, etc.) to look around and attain different visual perspectivesof the pipe. The captured image data may be viewed on a display screenby a user located at a remote location.

Conventionally, when observing pipe inspection image data displayed on ascreen, users may estimate the size of a potential defect or pipefeature that the user sees in the image data. This is done by anexperienced technician, with knowledge of the pipe size, estimating thesize of the feature. For example, on a display screen a crack in a pipemay appear over 1 inch of the display screen. However, since the displayscreen does not typically show the features in their actual size, theuser must estimate the actual size of the defect/feature. Accordingly,in this example, one user may estimate the actual size of the crack as 5inches long, while another user may estimate the actual size of thecrack as 4 inches long. Depending on the experience of the users viewingthe image data, the estimation may be relatively accurate. Experiencedusers may have familiarity with particular pipes and their correspondingdimensions, common objects found in those pipes, common defectsassociated with the pipes, and the like. However, due to the abundanceof different pipe types, pipe sizes, potential defects associated withthose pipes, and the like, even experienced users may be unable toprovide accurate estimations regarding parameters of particularvisualized pipe features.

Accordingly, an embodiment provides an accurate and precise method foranalyzing captured image data and providing additional informationassociated with at least one pipe feature in the image data to a user.In an embodiment, image data (e.g., still image data, video data, etc.)associated with a pipe may be received at a display screen. The imagedata may be obtained by a pipe inspection robot having a calibratedlens. The calibrated lens may be calibrated to accurately identifyfeature sizes and may allow for easy identification of the realdimensions of displayed pipe features. An embodiment may then receiveuser input (e.g., touch input, mouse input, etc.) on a portion of theimage data and analyze the portion of the image to identify at least onefeature (e.g., a defect, an object, etc.) associated with the input.Subsequent to identifying the feature, an embodiment may then providedata, using the characteristics of the calibrated lens, associated withthe identified feature (e.g., dimensions of the feature, angle of thefeature, identity of the feature, feature type, etc.). Such a methodenables users to attain accurate sizing and other characteristicinformation associated with an identified feature in a pipe.

The description now turns to the figures. The illustrated exampleembodiments will be best understood by reference to the figures. Thefollowing description is intended only by way of example and simplyillustrates certain selected example embodiments.

Referring now to FIG. 1, an exploded view of an example pipe inspectionrobot 10 is illustrated. The device may be utilized to navigate,explore, map, image, etc., various pipe environments (e.g., water pipes,sewer pipes, etc.). By way of example, the pipe inspection robot 10 maybe an autonomous or semi-autonomous mobile robot utilized for pipeinspections (e.g., inspection of a municipal wastewater or sewer pipe).However, it will be appreciated that the pipe inspection robot 10 may beembodied in any number of different types of inspection platforms,including non-autonomous devices and tele-operated inspection platforms,and may be utilized in a plurality of other environments.

The pipe inspection robot 10 includes a sensor portion 12 and a chassisportion 14. The sensor portion 12 is electrically and mechanicallycoupled to the chassis portion 14. The pipe inspection robot 10 may alsoinclude a riser portion 16 which is positioned between the sensorportion 12 and the chassis portion 14, and is electrically andmechanically coupled to each. The riser portion 16 operates to increasethe distance the sensor portion 12 is situated above the lowest portionof the pipe, and may be utilized in large pipe applications to provide adesired vantage point for various sensing devices of the sensor portion12. According to other embodiments, the pipe inspection robot 10 doesnot include the above-described riser portion 16.

Aspects of the pipe inspection robot 10 may be implemented by acomputing device and/or a computer program stored on a non-transitorycomputer-readable medium. The non-transitory computer-readable medium,for example, may comprise a disk or memory device on board the sensorportion 12. The pipe inspection robot 10 may also include distributedparts, e.g., forming part of a distributed system with a logically orphysically coupled computer system, for example including a processor,memory, display device and input device (not illustrated in FIG. 1).

According to an embodiment, the sensor portion 12 includes a pluralityof sensing devices, e.g., a camera or image sensor 24, a radar device, asonar device, an infrared device, a laser device, etc., for sensing theconditions within the pipe's interior, e.g., an interior wall of thepipe. The sensor portion 12 may also include a computing devicecommunicably coupled to the sensing devices and having a processor forprocessing raw information (e.g., raw image data) captured by thesensing devices, a memory device communicably coupled to the computingdevice for storing the raw and/or processed information, and controlcircuitry communicably coupled to the computing device for controllingvarious components of the pipe inspection robot 10, for examplecircuitry illustrated in FIG. 6. The memory device may also be utilizedto store software comprising a program of instructions, which isutilized by the pipe inspection robot 10 to navigate, explore, map,image, etc., the interior of the pipe.

The physical configuration of the pipe inspection robot 10 impacts thequality and type of images obtained by an image sensor 24 included inthe sensor portion 12. For example, a pipe inspection robot 10 thatincludes the riser portion 16 will have its sensor portion 12, andconsequently its image sensor 24, positioned differently with respect tothe interior pipe wall as compared to a configuration of the pipeinspection robot 10 that does not include the riser portion 16.

Similarly, other differences in the physical makeup of the pipeinspection robot 10 will impact the image quality obtained therewith.For example, the lens of the image sensor 24 included in sensor portion12 will affect the type of image data obtained. For example, awide-angle view lens used in camera 24, such as a fisheye lens, willobtain a different image than another type of lens, e.g., a lens that isnot a wide-angle lens. Furthermore, even within the same type of lens,the specific physical properties of the lens will affect the quality ofthe image obtained thereby. For example, lenses of the same type mayproduce different images, e.g., because of slight imperfections includedin the lenses, e.g., due to manufacturing tolerances, or postmanufacture effects such scratches or defects introduced into the lensafter it has been manufactured. Thus, depending on the type or qualitiesof the image sensor 24 components, such as the type or condition of thelens used by the image sensor 24, different image qualities andcharacteristics will be produced by the pipe inspection robot 10.

An embodiment permits users to obtain calibrated image data, for exampleimage data that takes into account the physical configuration of thepipe inspection robot 10. To produce the calibrated image data, e.g., aquantitative measure of a pipe feature, an embodiment employscalibration data. For example, the calibration data comprisesinformation such as the type of pipe inspection robot 10 used to obtainthe image data, the type of image sensor 24 used by the sensor portion12 to capture the image data, the type of lens employed with the imagesensor 24, the actual identification of the lens used with the imagesensor 24, etc. This permits an embodiment to calibrate the image datato take into account physical properties such that when the image isdisplayed on a display screen, the actual size of a pipe featurecontained within the image, e.g., as highlighted by the user, can beprovided as output. This process makes the evaluation of pipe features,such as a crack within a pipe's interior wall, easier and more accuratein that the image data can be processed to automatically obtain the sizeof the pipe feature, identify the pipe feature, etc.

Referring to FIG. 2, embodiments provide that certain calibrationmethods may be used to calibrate an image to produce quantitative pipefeature data. For example, a lens may be calibrated to characterize itsoptical properties, an inspection platform (e.g., pipe inspection robot10) may be characterized to identify its physical configuration andattributes, a pipe may be characterized in terms of its physicalproperties (e.g., dimensions, curvature, material construction, etc.)and the like. This information impacts that resultant image produced byan inspection platform such as pipe inspection robot 10, i.e., adifferent lens, a different physical configuration of the inspectionplatform, a different type of pipe, etc., will all produce differentimages of the pipe interior.

By way of example, and referring to FIG. 2, to calibrate a lens a usermay cover a wall in graph paper or other material having a regularlydefined pattern at 201 and capture an image of the wall with a lens orlens type at 202 to determine characteristics and aberrations of a lensor lens type by inspecting resultant image produced.

For example, an image analysis may be conducted to detect alterations inthe expected pattern within the image that are the result of distortionsproduced by the lens. The distortions produced in the pattern by thelens may be intended, e.g., in the example of certain wide angle typelenses, or may be unintentional, e.g., the result of a defect in thelens. If a distorted region is identified at 203, the distorted regionmay be characterized at 204. For example, a region within the image maybe warped, and the degree of warping within the region may becharacterized. This permits the computation of calibration data for theregion at 205, e.g., a de-warping effect that is to be applied to thisregion of the image, a notation that this region of the image is to beexcluded or not used in quantitative analysis, etc. The calibration datais then stored at 206 for use in later image processing and productionof quantitative pipe feature data.

Other types of lens calibration techniques may be utilized. For example,using a light source or other source behind the lens to cause aprojection of the lens onto graph paper or other projection area permitsusing the projection to make notes and marks of any defects in the lensand associate this information with the lens, for example, by saving itinto an accessible database, assigning it to a particular robot, and thelike. Additionally, the projection allows a person to make notesregarding the projection distance, depth, and details of how the lensprojects onto different objects.

In an embodiment, the extent of calibration may be associated with thequality of the lens type. Lower quality lenses may have more defects(e.g., blemishes, inclusions, other aberrations, etc.) than higherquality lenses. Additionally, in a lens set (e.g., a set of ten lenses,etc.), each of the lenses in the set may have different defects based onthe quality of the lenses in the set. Accordingly, lens calibration maybe required for each lens in the set. For example, in a set of ten lowquality lenses, each of the ten lenses may need to be calibrated becauseeach lens likely has defects particular to that lens. Alternatively, ina set of ten high quality lenses, only one of the ten lenses may need tobe calibrated and then that calibration data may be applied to the othernine lenses because the lenses in the high-quality set likely all havesubstantially the same characteristics.

As described herein, during the calibration process, other informationmay be obtained for completing the calibration. For example, toaccurately calibrate a lens, the distance between the lens and theprojection area, the distance between the light source and the lens, thesize of the projection, and the like, may be required. This informationmay be known beforehand, e.g., by storing the physical attributes of thepipe inspection robot 10 configuration, the dimension of the pipe, thelocation of the pipe inspection robot 10 within the interior of thepipe, and the like. Therefore, an embodiment may use a variety ofcalibration data, alone or in combination, to provide quantitative pipefeature data.

In an embodiment, image data may be gathered using one or more cameras24 provided in the sensor portion 12 of the pipe inspection robot 10. Inan embodiment, where more than one camera 24 is coupled to the pipeinspection robot 10, one or more of the cameras may contain a calibratedlens. In an embodiment, the image data captured by the camera(s) 24 maybe, by way of example and not limitation, still-image data or videoimage data and may be used to image the inner characteristics andcontents of a pipe (e.g., pipe wall features, taps, valves, physicalcontent flowing through the pipe, pipe defects, other content, etc.). Inan embodiment, the image data may be displayed to a user at aninformation handling device (e.g., laptop computer, desktop computer,tablet, smart phone, etc.) that may be in a remote location with respectto the pipe inspection robot 10 (e.g., an office, a laboratory, anotherlocation, etc.).

In an embodiment, the image data may be recorded and transmitted to aninformation handling device (e.g., remote computer) via a wired orwireless connection. The transmission may occur in real time (e.g.,immediately or substantially immediately) or may be delayed e.g., imagedata stored locally on the pipe inspection robot 10, for example if aconnection is unable to be established while the pipe inspection robotis in the pipe, etc. In an embodiment, the image data may be recordedand stored remotely (e.g., in the cloud, on another device, in othernetwork storage, on or with a website, etc.) and then accessed from aremote location.

After a pipe inspection robot 10 has captured image(s) of the interiorof a pipe, a user may utilize the images to obtain quantitative pipefeature data, for example according to the process illustrated in FIG.3. A pipe inspection robot 10 may provide image data regarding theinterior of a pipe at 301. This image data is displayed on a displayscreen for a user to review, as illustrated at 302. As explained,conventionally an experienced user or technician is required to make aneducated guess as to the identity of the feature (e.g., scratch, crack,hole, root intrusion, etc.) and as to the quantitative nature of thefeature (e.g., the length of a crack, the size of a hole, the percentarea of a blockage, etc.).

In contrast, using calibration data for the image, an embodimentprovides an automated pipe feature identification capability, includingthe ability to produce quantitative pipe feature data. For example, asillustrated at 303, an embodiment receives user input associated with atleast a portion of the image that is displayed on the display screen. Inan embodiment, the image displayed to a user may be interactive imagedata. For example, a user may interact with the image by providing userinputs. In an embodiment, user input may be provided using touch input,stylus input, mouse input, and the like. In an embodiment, the userinput may comprise a selecting action. The selection action may includehighlighting, circling, tracing, underlining, painting or otherselection actions that serve to designate a part of the image forfurther analysis. An embodiment may provide a visual indication (e.g., acolored line, a notification box, a highlighted portion, etc.) on thedisplay screen corresponding to the selection action. For example, auser interested in an object located on the top right portion of thedisplayed image may draw a circle (e.g., using touch input, etc.) aroundthat object. In another example, a user interested in a displayed crackin the image may trace (e.g., using stylus input, etc.) the length ofthe crack. In yet a further example, a user interested in a displayedcrack in the image may select the crack (e.g., using touch input, etc.)and then may subsequently be presented with a notification box withinformation regarded the crack, produced by an automated quantitativefeature process, as further described herein.

At 304, an embodiment may analyze the portion of the image associatedwith the user input. In an embodiment, the analysis may be conducted inorder to identify the presence of at least one feature. For example,image processing of image pixel data may be conducted to identify theboundaries of an object within the portion of the image selected by theuser input. The object may be identified as at least one pipe featureusing a variety of image processing techniques. For example, anembodiment may match an object contained within the area selected by theuser by matching its characteristics with that of known features. By wayof specific example, an embodiment may identify a crack in a pipe wallby analyzing pixels of image data in the area selected by the user inorder to identify object boundaries, e.g., using an edge detectionmechanism. An embodiment may thereafter match the identified objectboundaries with a known object or object set, e.g., a crack may beidentified based on detection of an object that is long with a minimalwidth, and is associated with depth data in the same region (e.g.,collected by another sensor of sensor portion 12, e.g., a laser sensor).The identified feature may be any feature associated with a pipe (e.g.,cracks in the pipe walls, intersecting taps, valves, physical objectssuch as roots intruding into the interior of the pipe, sediment buildup,pipe wall decay or erosion, other pipe features, etc.).

The analysis at 304 may include determining quantitative pipe featuredata or other information associated with a pipe feature. For example,an embodiment may use the calibration data (e.g., calibrated lensinformation) to determine quantitative information regarding theselected pipe feature. The quantitative analysis may include usingcalibration data associated with the calibrated lens, for example, aknown defect of the lens distorting an area in the image selected by theuser and containing the pipe feature, dimensions of the lens causingwarping of the image in a known manner, and/or other informationcaptured during calibration of the lens, and calibration data associatedwith the pipe and/or pipe inspection robot, e.g., physical dimensions ofthe pipe, physical configuration or set up of the pipe inspection robot10, etc. For example, an embodiment may use the size of the pipe (e.g.,5-inch diameter pipe) to translate the image data produced by the camera24 using the pipe dimensions. Accordingly, an embodiment may usecalibration data to account for image characteristics in the imagedisplayed in two dimensions to the user on the display screen. Thisallows an embodiment to determine that a three-dimensional featureidentified by a user, for example by tracing two inches along adisplayed image, corresponds in reality to a crack that is five incheslong because it traverses a curve in the pipe wall, is warped a certainamount by a wide-angle lens, etc. Thus, an embodiment adjusts the userinput data using the calibration data (e.g., lens calibration data, pipeinspection robot calibration data, pipe dimension calibration data,etc.).

The analysis at 304 may include accessing the calibrated lensinformation and obtaining the pipe parameter information. Obtaining pipeparameter information may be completed using different techniques. Onetechnique may include a user providing input identifying the pipeparameter information. For example, the user may provide information onthe size of the pipe, location of the pipe, location of the robot withinthe pipe, and the like. Another technique may include the pipeinspection robot 10 providing pipe information. For example, the pipeinspection robot 10 may be designed for a particular size pipe.Accordingly, the pipe inspection robot may provide the pipe informationto the system. The pipe parameter information may also be provided usingdifferent information. For example, based upon the location of the pipeinspection robot 10, the system may compare the geographic informationto pipe maps or other known pipe information to determine informationabout the pipe or other pipe parameters.

If at least one feature in the image data cannot be identified at 305,an embodiment may, at 306, prompt a user to re-select a feature in theimage. However, if at least one feature in the image data can beidentified at 305, an embodiment may provide data associated with thefeature at 307. An embodiment may utilize the calibrated lens data, forexample, in conjunction with the pipe information, to provide data(e.g., sizing data, identity data, other data, etc.) for identified pipefeatures displayed on the display screen. Such a method enables users toobtain more accurate information regarding pipe features they see on adisplay screen. For example, a 4-inch crack in an 8-inch pipe and an8-inch crack in a 16-inch pipe may look the same on a display screen. Bygathering pipe image data of the 8-inch pipe using a lens calibrated tothe dimensional aspects of the 8-inch pipe, an embodiment is able todetermine that the displayed crack is 4 inches, not 8 inches, despitethe fact that the 4-inch crack and the 8-inch crack occupy the samenumber of pixels in different images on the display.

In an embodiment, the data associated with the pipe feature may comprisesize data associated with the pipe feature (e.g., length data, widthdata, height data, area data, percentage area, other size data, etc.).As illustrated in FIG. 4, for example, in a display screen 400 aincluding a touch screen or coupled to another input device, a user maycircle a portion 401 of a displayed image 400 of a pipe 402 thatincludes a pipe feature 403 such as a crack. An embodiment may thenanalyze the pipe feature 403, e.g., including use of the calibrated lensdata or other calibration data for the corresponding image 400, todetermine actual size information for the crack 403. An embodiment maythen provide the size information to a user as output data 404. In anembodiment, the sizing information may be presented to a user as output(e.g., textual or other visual output, audible output, etc.). Forexample, an embodiment provides the data 404 “Feature: Crack; Length: 4in; Max Width: 0.5 in,” to a user in a text box co-located somewhere onthe displayed image, in a text box co-located on the displayed imagenear the crack, as text information in another location, audibly, or thelike.

In an embodiment, the data 404 associated with the pipe feature maycomprise other data. An embodiment may analyze a selected portion of thedisplay for a pipe feature and then provide, based on identifiedcharacteristics of the pipe feature (e.g., identified size, diameter,etc.) a best-guess as to what the pipe feature is. For example, a usermay circle a portion 401 of a displayed image 400 comprising an unknownpipe feature 403. An embodiment may analyze the image portion 401 toidentify characteristics associated with the pipe feature 403 andcompare these identified characteristics against stored characteristicsassociated with known objects (e.g., stored in a database, stored in alookup table, accessible online, etc.) and/or characteristics associatedwith objects known to exist in the corresponding pipe. An embodiment maythen, based on the comparison, provide a best-guess as to the identityof the pipe feature 403. In an embodiment, the best-guess may bepresented to a user as output 404 (e.g., textual output, audible output,etc.). For example, an embodiment may provide the following best-guessidentity information, “This feature is likely a crack,” to a user usingaforementioned output methods.

In an embodiment, size data may be provided in conjunction with theidentity data. For example, an embodiment may provide (e.g., using theaforementioned output methods) the following information to a user:“This feature is likely a tap and it measure 8 inches in diameter.” Anembodiment may identify all detected pipe features in a displayed image400 and provide data for all of the pipe features, e.g., feature 403,irrespective if the user has provided input to highlight or select thefeature. For example, an embodiment may display an image 400 associatedwith a pipe 402 and then provide (e.g., automatically, responsive toreceiving a user indication, etc.) identity and/or sizing informationfor each pipe feature 403 identified in the displayed image 400.

In an embodiment, data associated with a pipe feature 403 may beprovided in real time as the image data is being received. For example,an embodiment may be receiving (e.g., wirelessly, etc.) pipe image datathrough a live feed. The live feed may be constantly analyzed (e.g.,every second, every 5 seconds, at another predetermined interval, etc.)to identify any pipe features captured in the pipe image data.Subsequent to identifying a pipe feature, an embodiment may provide(e.g., using the aforementioned output methods) data regarding that pipefeature to a user, e.g., as indicated at 404.

The various embodiments described herein thus represent a technicalimprovement to identifying and providing additional informationassociated with objects and/or features displayed in pipe image data.Using the techniques described herein, an embodiment may use a pipeinspection robot to gather pipe image data through a calibrated lensthat is calibrated based on the dimensional aspects of a particularpipe. An embodiment may then analyze a portion of the pipe image data inorder to identify a feature of the pipe and then provide data associatedwith that pipe feature. Such techniques provide a more accurate way ofdetermining the identify and sizing characteristics of various featuresin a pipe.

It will be readily understood that certain embodiments can beimplemented using any of a wide variety of devices or combinations ofdevices. Referring to FIG. 5, an example device that may be used inimplementing one or more embodiments includes a computing device(computer) 510, for example included in a pipe inspection robot 10and/or a computer system providing the display of pipe images in adisplay screen.

The computer 510 may execute program instructions configured to storeand analyze pipe data and perform other functionality of theembodiments, as described herein. Components of computer 510 mayinclude, but are not limited to, a processing unit 520, a system memory530, and a system bus 522 that couples various system componentsincluding the system memory 530 to the processing unit 520. The computer510 may include or have access to a variety of computer readable media.The system memory 530 may include computer readable storage media in theform of volatile and/or nonvolatile memory devices such as read onlymemory (ROM) and/or random access memory (RAM). By way of example, andnot limitation, system memory 530 may also include an operating system,application programs, other program modules, and program data. Forexample, system memory 530 may include application programs such as pipeinspection software, e.g., missions, image capture routines, imageprocessing routines, etc. Further, system memory 530 may includecalibration data as described herein, that may be predetermined,determined dynamically (e.g., while conducting a pipe inspectionmission), or a combination thereof. The calibration data may betransmitted by wired or wireless communication, e.g., from pipeinspection robot 10 to another computing device, independently, as partof the image data, or a combination of the foregoing.

A user can interface with (for example, enter commands and information)the computer 510 through input devices 540 such as a touch screen, astylus and digitizer pair, a mouse, or a touch pad. A monitor or othertype of display screen or device can also be connected to the system bus522 via an interface, such as interface 550. For example, the displayscreen 400 a of FIG. 4 may be coupled to the computer circuitry viaoutput interface 550. In addition to a monitor, computers may alsoinclude other peripheral output devices. The computer 510 may operate ina networked or distributed environment using logical connections to oneor more other remote computers or databases. The logical connections mayinclude a network, such local area network (LAN) or a wide area network(WAN), but may also include other networks/buses.

It should be noted that the various functions described herein may beimplemented using processor executable instructions stored on anon-transitory storage medium or device. A non-transitory storage devicemay be, for example, an electronic, electromagnetic, or semiconductorsystem, apparatus, or device, or any suitable combination of theforegoing. More specific examples of a non-transitory storage mediuminclude the following: a portable computer diskette, a hard disk, arandom-access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), a portablecompact disc read-only memory (CD-ROM), or any suitable combination ofthe foregoing. In the context of this document “non-transitory” includesall media except non-statutory signal media.

Program code embodied on a non-transitory storage medium may betransmitted using any appropriate medium, including but not limited towireless, wireline, optical fiber cable, RF, etc., or any suitablecombination of the foregoing.

Program code for carrying out operations may be written in anycombination of one or more programming languages. The program code mayexecute entirely on a single device, partly on a single device, as astand-alone software package, partly on single device and partly onanother device, or entirely on the other device. In some cases, thedevices may be connected through any type of connection or network,including a local area network (LAN) or a wide area network (WAN), orthe connection may be made through other devices (for example, throughthe Internet using an Internet Service Provider), through wirelessconnections, or through a hard wire connection, such as over a USBconnection.

Example embodiments are described herein with reference to the figures,which illustrate example methods, devices and program products accordingto various example embodiments. It will be understood that the actionsand functionality may be implemented at least in part by programinstructions. These program instructions may be provided to a processorof a device to produce a special purpose machine, such that theinstructions, which execute via a processor of the device implement thefunctions/acts specified.

It is worth noting that while specific blocks are used in the figures,and a particular ordering of blocks has been illustrated, these arenon-limiting examples. In certain contexts, two or more blocks may becombined, a block may be split into two or more blocks, or certainblocks may be re-ordered or re-organized or omitted as appropriate, asthe explicit illustrated examples are used only for descriptive purposesand are not to be construed as limiting.

As used herein, the singular “a” and “an” may be construed as includingthe plural “one or more” unless clearly indicated otherwise.

This disclosure has been presented for purposes of illustration anddescription but is not intended to be exhaustive or limiting. Manymodifications and variations will be apparent to those of ordinary skillin the art. The example embodiments were chosen and described in orderto explain principles and practical application, and to enable others ofordinary skill in the art to understand the disclosure for variousembodiments with various modifications as are suited to the particularuse contemplated.

Thus, although illustrative example embodiments have been describedherein with reference to the accompanying figures, it is to beunderstood that this description is not limiting and that various otherchanges and modifications may be affected therein by one skilled in theart without departing from the scope or spirit of the disclosure.

What is claimed is:
 1. A method, comprising: displaying, at a displayscreen, an image of an interior of a pipe, the image being obtainedusing a pipe inspection robot and comprising at least one visiblefeature; accessing, using a processor, calibration data associated withthe image; receiving, via an input device, user input marking at least aportion of the image comprising the at least one visible feature;determining, using a processor, quantitative pipe feature data for theat least one visible feature of the pipe using the marking and thecalibration data; and displaying on the display screen, based on thedetermining, the quantitative pipe feature data associated with the atleast one visible feature in response to the user input.
 2. The methodof claim 1, wherein the calibration data comprises one or more of datarelated to a lens and data related to a lens type.
 3. The method ofclaim 1, wherein the calibration data comprises data related to a sizeof the pipe and a view of the pipe.
 4. The method of claim 3, whereinthe data related to a view of the pipe comprises a relative viewingangle of the image.
 5. The method of claim 1, wherein the calibrationdata comprises data related to a physical configuration of the pipeinspection robot.
 6. The method of claim 1, further comprisingautomatically identifying the at least one visible feature.
 7. Themethod of claim 1, wherein the quantitative pipe feature data comprisesa length or width of the at least one visible feature.
 8. The method ofclaim 1, wherein the quantitative pipe feature data comprises an area ofthe at least one visible feature.
 9. The method of claim 1, wherein theuser input comprises one or more of a selection input, a trace input,and a highlight input.
 10. The method of claim 1, wherein the providingcomprises providing pipe feature size data responsive to the user input.11. A system, comprising: an information handling device comprising adisplay screen, an input device, a processor, and a memory device thatstores instructions executable by the processor to: display, at thedisplay screen, an image of an interior of a pipe, the image beingobtained using a pipe inspection robot and comprising at least onevisible feature; access calibration data associated with the image;receive, via the input device, user input marking at least a portion ofthe image comprising the at least one visible feature; determinequantitative pipe feature data for the at least one visible feature ofthe pipe using the marking and the calibration data; and display, basedon the determination of the quantitative pipe feature data, thequantitative pipe feature data associated with the at least one visiblefeature in response to the user input.
 12. The system of claim 11,wherein the calibration data comprises one or more of data related to alens and data related to a lens type.
 13. The system of claim 11,wherein the calibration data comprises data related to a size of thepipe and a view of the pipe.
 14. The system of claim 13, wherein thedata related to a view of the pipe comprises a relative viewing angle ofthe image.
 15. The system of claim 11, wherein the calibration datacomprises data related to a physical configuration of the pipeinspection robot.
 16. The system of claim 11, further comprisingautomatically identifying the at least one visible feature.
 17. Thesystem of claim 11, wherein the quantitative pipe feature data comprisesa length or width of the at least one visible feature.
 18. The system ofclaim 11, wherein the quantitative pipe feature data comprises an areaof the at least one visible feature.
 19. The system of claim 11, whereinthe user input comprises one or more of a selection input, a traceinput, and a highlight input.
 20. A product, comprising: anon-transitory storage device that stores code executable by aprocessor, the code comprising: code that displays, at a display screen,an image of an interior of a pipe, the image being obtained using a pipeinspection robot and comprising at least one visible feature; code thataccesses calibration data associated with the image; code that receivesuser input marking at least a portion of the image comprising the atleast one visible feature; code that determines quantitative pipefeature data for the at least one visible feature associated with thepipe using the marking and the calibration data; and code that displays,based on the determination of the quantitative pipe feature data, thequantitative pipe feature data associated with the at least one visiblefeature in response to the user input.